The fake news graph analyzer: An open-source software for characterizing spreaders in large diffusion graphs

Abstract

In the study of fake news spreading, it is essential to know how different types of spreaders differ in terms of their characteristics, interconnections, and cascading flow. The fake news graph analyzer (FNGA) is an open-source software that provides the required computations for such extended analyses on large graphs. Moreover, FNGA generates data for graph visualizations. Also, FNGA is designed to consider the spreading of both fake and true news simultaneously in the graph, leading to a variety of confrontational patterns. FNGA facilitates future research on fake news and the diffusion of any contagion within a graph of entities.

The Rumor Categorizer: An open-source software for analyzing rumor posts on Twitter

“…The former level of analysis provides the categorization and extraction of user data with respect to each category, while the latter aids in the detection of wavelike forms of diffusion. Also, recently a similar approach has been taken into account for fake news analysis but with a focus on the underlying graphs [17]. The latter level of analysis helps with the extraction of wavelike forms of diffusions.…”